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Proceedings Paper

A comparative study of multi-focus image fusion validation metrics
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Paper Abstract

Fusion of visual information from multiple sources is relevant for applications security, transportation, and safety applications. One way that image fusion can be particularly useful is when fusing imagery data from multiple levels of focus. Different focus levels can create different visual qualities for different regions in the imagery, which can provide much more visual information to analysts when fused. Multi-focus image fusion would benefit a user through automation, which requires the evaluation of the fused images to determine whether they have properly fused the focused regions of each image. Many no-reference metrics, such as information theory based, image feature based and structural similarity-based have been developed to accomplish comparisons. However, it is hard to scale an accurate assessment of visual quality which requires the validation of these metrics for different types of applications. In order to do this, human perception based validation methods have been developed, particularly dealing with the use of receiver operating characteristics (ROC) curves and the area under them (AUC). Our study uses these to analyze the effectiveness of no-reference image fusion metrics applied to multi-resolution fusion methods in order to determine which should be used when dealing with multi-focus data. Preliminary results show that the Tsallis, SF, and spatial frequency metrics are consistent with the image quality and peak signal to noise ratio (PSNR).

Paper Details

Date Published: 31 May 2016
PDF: 9 pages
Proc. SPIE 9841, Geospatial Informatics, Fusion, and Motion Video Analytics VI, 98410J (31 May 2016); doi: 10.1117/12.2224349
Show Author Affiliations
Michael Giansiracusa, Indiana Univ. of Pennsylvania (United States)
Adam Lutz, Indiana Univ. of Pennsylvania (United States)
Neal Messer, Indiana Univ. of Pennsylvania (United States)
Soundararajan Ezekiel, Indiana Univ. of Pennsylvania (United States)
Mark Alford, Air Force Research Lab. (United States)
Erik Blasch, Air Force Research Lab. (United States)
Adnan Bubalo, Air Force Research Lab. (United States)
Michael Manno, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 9841:
Geospatial Informatics, Fusion, and Motion Video Analytics VI
Matthew F. Pellechia; Kannappan Palaniappan; Peter J. Doucette; Shiloh L. Dockstader; Gunasekaran Seetharaman; Paul B. Deignan, Editor(s)

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